
The grouped asymmetric kernel [1]} is used in the CNN layer (known as ACNet), which strengthens the kernel selection function and is robust to layer parameters. It has been shown in many previous works [2]}[3]} that this performs better than a single wide CNN layer.

The residual link [4]} is used to provide high resolution learning with deeper stacked layers. Since the CNN suffers from the vanishing gradient problem and degrades performance with a higher number of stacked layers, use of the residual link allows a layer to directly learn the residual of the previous layer's output, which enhances the minor profile.

